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pro vyhledávání: '"P., Raghavendra"'
We study to which extent additive fairness metrics (statistical parity, equal opportunity and equalized odds) can be influenced in a multi-class classification problem by memorizing a subset of the population. We give explicit expressions for the bia
Externí odkaz:
http://arxiv.org/abs/2412.09254
Autor:
Nandi, Anuj, Singh, Swapnil, Jaiswal, Bhavesh, Jain, Anand, Verma, Smrati, Palawat, Reenu, T., Ravishankar B., Singh, Brajpal, Tyagi, Anurag, Das, Priyanka, Bose, Supratik, Verma, Supriya, Gautam, Waghmare Rahul, R., Yogesh Prasad K., Raha, Bijoy, Mendhekar, Bhavesh, K., Sathyanaryana Raju, V., Srinivasa Rao Kondapi, Kumar, Sumit, Thakur, Mukund Kumar, Bhatia, Vinti, Sharma, Nidhi, Yenni, Govinda Rao, Satya, Neeraj Kumar, Raghavendra, Venkata, S., Vivechana M., Justin, Evangelin Leeja, Karmakar, Praloy, Patra, Anurag, J., Naga Manjusha, Srikanth, Motamarri, Rajhans, Chinmay Kumar, K., Kalpana, P, Veeramuthuvel
SHAPE (Spectro-polarimetry of HAbitable Planet Earth) is an experiment onboard the Chandrayaan-3 Mission, designed to study the spectro-polarimetric signatures of the habitable planet Earth in the near-infrared (NIR) wavelength range (1.0 - 1.7 $\mu$
Externí odkaz:
http://arxiv.org/abs/2412.07416
The upper mid-band (or FR3, spanning 6-24 GHz) is a crucial frequency range for next-generation mobile networks, offering a favorable balance between coverage and spectrum efficiency. From another perspective, the systems operating in the near-field
Externí odkaz:
http://arxiv.org/abs/2412.02815
Autor:
Rao, P Raghavendra, Vyavahare, Pooja
This work studies the distributed learning process on a network of agents. Agents make partial observation about an unknown hypothesis and iteratively share their beliefs over a set of possible hypotheses with their neighbors to learn the true hypoth
Externí odkaz:
http://arxiv.org/abs/2411.11411
In the domain of Extended Reality (XR), particularly Virtual Reality (VR), extensive research has been devoted to harnessing this transformative technology in various real-world applications. However, a critical challenge that must be addressed befor
Externí odkaz:
http://arxiv.org/abs/2411.10489
Autor:
Sharma, Geetanjali, Tandon, Abhishek, Jaswal, Gaurav, Nigam, Aditya, Ramachandra, Raghavendra
Iris recognition technology plays a critical role in biometric identification systems, but their performance can be affected by variations in iris pigmentation. In this work, we investigate the impact of iris pigmentation on the efficacy of biometric
Externí odkaz:
http://arxiv.org/abs/2411.08490
This study sought to better understand the causes of price disparity in cesarean sections, using newly released hospital data. Beginning January 1, 2021, Centers for Medicare and Medicaid Services (CMS) requires hospitals functioning in the United St
Externí odkaz:
http://arxiv.org/abs/2411.08174
Autor:
Sayana, Krishna, Vasudeva, Raghavendra, Vasilevski, Yuri, Su, Kun, Hebert, Liam, Pine, James, Pham, Hubert, Jash, Ambarish, Sodhi, Sukhdeep
The recent advances in Large Language Model's generation and reasoning capabilities present an opportunity to develop truly conversational recommendation systems. However, effectively integrating recommender system knowledge into LLMs for natural lan
Externí odkaz:
http://arxiv.org/abs/2410.16780
Autor:
Vasudevan, Ekamresh, Sridhara, Shashank N., Pavez, Eduardo, Ortega, Antonio, Singh, Raghavendra, Kalluri, Srinath
We present a novel method to correct flying pixels within data captured by Time-of-flight (ToF) sensors. Flying pixel (FP) artifacts occur when signals from foreground and background objects reach the same sensor pixel, leading to a confident yet inc
Externí odkaz:
http://arxiv.org/abs/2410.08084
Autor:
PN, Aravinda Reddy, Ramachandra, Raghavendra, Venkatesh, Sushma, Rao, Krothapalli Sreenivasa, Mitra, Pabitra, Krishna, Rakesh
Face recognition systems (FRS) can be compromised by face morphing attacks, which blend textural and geometric information from multiple facial images. The rapid evolution of generative AI, especially Generative Adversarial Networks (GAN) or Diffusio
Externí odkaz:
http://arxiv.org/abs/2410.07625